Evaluation of four ELISA assays to diagnose Mycobacterium tuberculosis complex infection in pigs

Resumen del trabajo presentado al 8th European Symposium of Porcine Health Management and 24th International Pig Veterinary Society Congress, celebrados en Dublin (Irlanda) del 7 al 10 de junio de 2016.[Introduction]: In countries in which bovine tuberculosis (bTB) is still prevalent or is re-emerging the contact among different animal species in extensive systems may contribute to the circulation of Mycobacterium bovis and other members of the Mycobacterium tuberculosis complex (MTC) and the spread of this disease. Thus, free-range pigs may be infected by MTC, developing subclinical infections, which are not detected until meat inspection procedures at slaughterhouse. Serodiagnosis has been recently proposed as a reliable screening tool for detecting infected herds. In this study four ELISA assays using different M. bovis peptides/proteins (MPB70+MPB83, INGENASA; treated bovine purified protein derivative, t-bPPD; bPPD1; and bPPD2 VACUNEK) as coating antigens were evaluated to diagnose MTC infection in pigs. [Materials and Methods]: Submandibular lymph nodes (SLN) and blood samples from 129 free-range pigs raised on Southern Spain farms with a history of condemnation due to tuberculosis-like lesions were sampled at slaughterhouse. SLN were tested by gross examination, histopathology, bacteriological culture and qPCR. Ninety-seven out of these animals were classified as bTB positive cases (compatible lesions and MTC detection by means of culture and qPCR) or bTB negative cases (absence of compatible lesions and negative MTC detection) and used as reference method. When necessary different cut-off values were evaluated. [Results]: All assays had a very good concordance between them (k ≥ 0.82). The MPB70+MPB83 based ELISA had the best sensitivity (Se) (78%, CI95 67.4%>88.5%) and a good concordance with the reference method (k=0.69). The t-bPPD and the bPPD1 in-house assays presented a slightly reduced Se (71.2%, CI95 59.6%>82.7%; and 66.1%, CI95 54%>78.2%; respectively) and a moderate concordance with the reference method (k=0.57 and 0.52, respectively). When the bPPD2 based ELISA was evaluated, similar Se to the previous ones was obtained using a cut-off of 0.35 (Se: 66.1%, CI95 54%>78.2%; k=0.52). Conclusion` +: These results suggest that despite the fact that MPB70+MPB83 ELISA presented the best results all four evaluated ELISA assays could be used as a screening tool to conduct TB surveillance in pigs at a population level. In addition, a cut-off of 0.35 is recommended for bPPD2 ELISA in order to obtain better diagnostic values.This study was financially supported by the Council of Economy, Science, Innovation and Employment of the Andalusian Government (AGR-2685-2012) and by the European Project WILDTBVAC (FP7-KBBE-613799).Peer Reviewe

Micro Scalable Graphene Oxide Productions Using Controlled Parameters in Bench Reactor

The detailed study of graphene oxide (GO) synthesis by changing the graphite/oxidizing reagents mass ratios (mG/mROxi), provided GO nanosheets production with good yield, structural quality, and process savings. Three initial samples containing different amounts of graphite (3.0 g, 4.5 g, and 6.0 g) were produced using a bench reactor under strictly controlled conditions to guarantee the process reproducibility. The produced samples were analyzed by Raman spectroscopy, atomic force microscopy (AFM), x-ray diffraction (XDR), X-ray photoelectron spectroscopy (XPS), Fourier-transform infrared spectroscopy (FTIR) and thermogravimetry (TGA) techniques. The results showed that the major GO product comprised of nanosheets containing between 1–5 layers, with lateral size up to 1.8 µm. Therefore, it was possible to produce different batches of graphene oxide with desirable physicochemical characteristics, keeping the amount of oxidizing reagent unchanged. The use of different proportions (mG/mROxi) is an important strategy that provides to produce GO nanostructures with high structural quality and scale-up, which can be well adapted in medium-sized bench reactor

Cannabidiol, a Cannabis sativa constituent, as an anxiolytic drug

Objectives: To review and describe studies of the non-psychotomimetic constituent of Cannabis sativa, cannabidiol (CBD), as an anxiolytic drug and discuss its possible mechanisms of action. Method: The articles selected for the review were identified through searches in English,articles, and book chapters were handsearched for additional references. Experimental animal and human studies were included, with no time restraints. Results: Studies using animal models of anxiety and involving healthy volunteers clearly suggest an anxiolytic-like effect of CBD. like", and "cannabidiol and anxiety". The reference lists of the publications included, review Portuguese, and Spanish in the electronic databases ISI Web of Knowledge, SciELO, PubMed, and PsycINFO, combining the search terms "cannabidiol and anxiolytic", "cannabidiol and anxiolytic-articles, and book chapters were handsearched for additional references. Experimental animal and human studies were included, with no time restraints. Results: Studies using animal models of anxiety and involving healthy volunteers clearly suggest an anxiolytic-like effect of CBD. Moreover, CBD was shown to reduce anxiety in patients with social anxiety disorder. Conclusion: like", and "cannabidiol and anxiety". The reference lists of the publications included, review Future clinical trials involving patients with different anxiety disorders are warranted, especially of panic disorder, obsessive-compulsive disorder, social anxiety disorder, and post-traumatic stress disorders. The adequate therapeutic window of CBD and the precise mechanisms involved in its anxiolytic action remain to be determined.Global Research Awards for Nicotine Dependence (GRAND) from Pfizer U.S.Global Research Awards for Nicotine Dependence (GRAND) from Pfizer U.S

Development of a Novel Anti-CD19 Chimeric Antigen Receptor : A Paradigm for an Affordable CAR T Cell Production at Academic Institutions

Genetically modifying autologous T cells to express an anti-CD19 chimeric antigen receptor (CAR) has shown impressive response rates for the treatment of CD19+ B cell malignancies in several clinical trials (CTs). Making this treatment available to our patients prompted us to develop a novel CART19 based on our own anti-CD19 antibody (A3B1), followed by CD8 hinge and transmembrane region, 4-1BB- and CD3z-signaling domains. We show that A3B1 CAR T cells are highly cytotoxic and specific against CD19+ cells in vitro, inducing secretion of pro-inflammatory cytokines and CAR T cell proliferation. In vivo, A3B1 CAR T cells are able to fully control disease progression in an NOD.Cg-Prkdc Il2rd/SzJ (NSG) xenograph B-ALL mouse model. Based on the pre-clinical data, we conclude that our CART19 is clearly functional against CD19+ cells, to a level similar to other CAR19s currently being used in the clinic. Concurrently, we describe the implementation of our CAR T cell production system, using lentiviral vector and CliniMACS Prodigy, within a medium-sized academic institution. The results of the validation phase show our system is robust and reproducible, while maintaining a low cost that is affordable for academic institutions. Our model can serve as a paradigm for similar institutions, and it may help to make CAR T cell treatment available to all patients

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio